Study Of B Ultrasonic Image Processing To Determine The HIFU Treatment Area

In recent years, the developing of the technology of ultrasonic diagnosis to mature, ultrasound treatment technology also developed. High intensity focused ultrasound (HIFU) treatment system is non-invasive tumor treatment technology, it is developing very fast in recent years, the ultrasound treatment system combines automatic control, image processing and computer technology, with noninvasive, without side-effects, and other notable features. HIFU treatment system -Digital image processing subsystem is a very important part, the important basis of preoperative and postoperative check monitoring. Therefore, real-time access B ultrasonic image, and the image processing, access accurate tumor area, real-time display treatment organization feature, is the key technology of HIFU cancer treatment.For the features and functionality of HIFU treatment system - image processing subsystem, using the B-dedicated video capture card to realize image processing subsystem, and meet the requirements of acquisition real-time image, it is simple and affordable. AVER EZCapture captures image to PC, firstly pre-processing the image, and then enhance the image and detect edge to determine lesion area. Studying the traditional image denoising and edge detection algorithms, combination with B ultrasonic image's characteristics, using the new threshold function of the wavelet threshold denoising algorithm to preprocess B ultrasonic image. Using Matlab7.4.0 simulating and calculating SNR to proved that:comparing with neighborhood average and median filtering,the wavelet threshold denoising algorithm not only suppress speckle noise well, but also reserve the effective information. Combine wavelet modulus maxima edge detection with fuzzy algorithm of edge detection operators to extract B ultrasonic image edge when extracting edge for sure lesions area. Through a lot of simulation experiments and compared with the traditional edge detection algorithm, wavelet and fuzzy algorithm can detect edge effectively, edge information more plentiful, it can detect lesions area edge effectively.